Investigating the effect of STN-DBS stimulation and different frequency settings on the acoustic-articulatory features of vowels

Yılmaz, Atilla; Sarac, Elif Tugba; Aydınlı, Fatma Esen; Yıldızgören, Mustafa Turgut; Okuyucu, Emine Esra; Serarslan, Yurdal

doi:10.1007/s10072-018-3479-y

Cited by 7 publications

(4 citation statements)

References 27 publications

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“…In our study, we used audio features from the Praat software because of their simplicity and wide adoption in speech research. [28][29][30] We also tested MFCC features with our machine learning model. Although MFCC 2 and 12 were significantly associated with pain scores in the univariate mixed model analysis, this did not translate to an improved KNN model accuracy compared with the KNN model trained with Praat features.…”

Section: Discussionmentioning

confidence: 99%

Daily Pain Prediction Using Smartphone Speech Recordings of Patients With Spine Disease

et al. 2023

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BACKGROUND: Pain evaluation remains largely subjective in neurosurgical practice, but machine learning provides the potential for objective pain assessment tools. OBJECTIVE: To predict daily pain levels using speech recordings from personal smartphones of a cohort of patients with diagnosed neurological spine disease. METHODS: Patients with spine disease were enrolled through a general neurosurgical clinic with approval from the institutional ethics committee. At-home pain surveys and speech recordings were administered at regular intervals through the Beiwe smartphone application. Praat audio features were extracted from the speech recordings to be used as input to a K-nearest neighbors (KNN) machine learning model. The pain scores were transformed from a 0 to 10 scale to low and high pain for better discriminative capacity. RESULTS: A total of 60 patients were enrolled, and 384 observations were used to train and test the prediction model. Using the KNN prediction model, an accuracy of 71% with a positive predictive value of 0.71 was achieved in classifying pain intensity into high and low. The model showed 0.71 precision for high pain and 0.70 precision for low pain. Recall of high pain was 0.74, and recall of low pain was 0.67. The overall F1 score was 0.73. CONCLUSION: Our study uses a KNN to model the relationship between speech features and pain levels collected from personal smartphones of patients with spine disease. The proposed model is a stepping stone for the development of objective pain assessment in neurosurgery clinical practice.

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Section: Discussionmentioning

confidence: 99%

Daily Pain Prediction Using Smartphone Speech Recordings of Patients With Spine Disease

et al. 2023

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“…Studies consistently indicate that LF stimulation of STN has a positive impact on speech [108,177,178]. One study showed improvements in the articulation of certain vowels at 130 Hz [179] and a significant increase in maximal phonation time (MPT) at 60 Hz compared to 130 Hz and OFF condition following STN-DBS [180]. Moreover, a combination of higher voltage and lower frequency and pulse width has been linked to enhancement of speech outcomes [181].…”

Section: Phonation and Articulationmentioning

confidence: 99%

“…Moreover, a combination of higher voltage and lower frequency and pulse width has been linked to enhancement of speech outcomes [181]. On the other hand, higher frequency stimulation may have variable effects on vocal control and production, with some studies reporting improvements in vocal production [179], while others suggest a negative impact [180,182]. However, no statistically significant differences were found in vocal acoustic measurements between low-frequency (60 Hz) and high-frequency (130 Hz) stimulation [172].…”

Section: Phonation and Articulationmentioning

confidence: 99%

Speech, voice, and language outcomes following deep brain stimulation: A systematic review

Tabari,

Berger,

Flouty

et al. 2024

PLoS ONE

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Background Deep brain stimulation (DBS) reliably ameliorates cardinal motor symptoms in Parkinson’s disease (PD) and essential tremor (ET). However, the effects of DBS on speech, voice and language have been inconsistent and have not been examined comprehensively in a single study. Objective We conducted a systematic analysis of literature by reviewing studies that examined the effects of DBS on speech, voice and language in PD and ET. Methods A total of 675 publications were retrieved from PubMed, Embase, CINHAL, Web of Science, Cochrane Library and Scopus databases. Based on our selection criteria, 90 papers were included in our analysis. The selected publications were categorized into four subcategories: Fluency, Word production, Articulation and phonology and Voice quality. Results The results suggested a long-term decline in verbal fluency, with more studies reporting deficits in phonemic fluency than semantic fluency following DBS. Additionally, high frequency stimulation, left-sided and bilateral DBS were associated with worse verbal fluency outcomes. Naming improved in the short-term following DBS-ON compared to DBS-OFF, with no long-term differences between the two conditions. Bilateral and low-frequency DBS demonstrated a relative improvement for phonation and articulation. Nonetheless, long-term DBS exacerbated phonation and articulation deficits. The effect of DBS on voice was highly variable, with both improvements and deterioration in different measures of voice. Conclusion This was the first study that aimed to combine the outcome of speech, voice, and language following DBS in a single systematic review. The findings revealed a heterogeneous pattern of results for speech, voice, and language across DBS studies, and provided directions for future studies.

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“…Die Stimulationsfrequenz beträgt durchschnittlich 130 Hz. Klinische Beobachtungen und erste Studien zeigten, dass eine hohe Frequenz für die Verbesserung des Tremors von Vorteil sein könnte, wohingegen das Sprechen und der Gang von einer niedrigen Frequenz profitieren (in den Studien definiert als Werte zwischen 60 Hz 71 72 und 110 Hz). Allerdings könnte die allmähliche Rückkehr von Tremor und Akinesie nach etwa 3 Monaten eine Erhöhung der Frequenz auf 130 Hz erforderlich machen 73 .…”

Section: Variabilität Der Sprachreaktion Auf Die Stimulationunclassified

Elektrische Stimulation tiefer Hirnstrukturen: Auswirkungen auf das Sprechen

Tripoliti¹,

Ramig²

2022

Sprache · Stimme · Gehör

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Die elektrische Stimulation tiefer Hirnstrukturen kann bei Parkinson-Patienten zu einer Verschlechterung des Sprechens und der Stimme führen. Dabei sind die Auswirkungen individuell unterschiedlich und von anatomisch, klinisch-therapeutischen und neurochirurgischen Faktoren abhängig. Teamarbeit zwischen den Berufsgruppen Neurochirurgie/ Neurologie und Sprachtherapie ist notwendig, um mit einer THS und logopädischen Therapie die bestmöglichen Behandlungserfolge zu erzielen.

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Investigating the effect of STN-DBS stimulation and different frequency settings on the acoustic-articulatory features of vowels

Cited by 7 publications

References 27 publications

Daily Pain Prediction Using Smartphone Speech Recordings of Patients With Spine Disease

Daily Pain Prediction Using Smartphone Speech Recordings of Patients With Spine Disease

Speech, voice, and language outcomes following deep brain stimulation: A systematic review

Elektrische Stimulation tiefer Hirnstrukturen: Auswirkungen auf das Sprechen

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